What is the difference between Apache Storm and Apache Spark?

Apache Storm and Apache Spark are both frameworks used for real-time data processing, but they have different architectures and use cases. Apache Storm is designed specifically for stream processing. It processes data in real-time as it arrives, making it ideal for applications that require low-latency processing, such as real-time analytics, monitoring, and alerting. Storm operates on a continuous basis, processing each piece of data as it flows through the system. On the other hand, Apache Spark is a more general-purpose framework that supports both batch and stream processing. While Spark Streaming can handle real-time data processing, it does so by dividing the data into micro-batches, which are processed in small increments of time. Spark also provides libraries for batch processing, interactive queries, machine learning, and graph processing, making it suitable for a wide range of use cases beyond just real-time processing. In summary, Apache Storm is focused solely on real-time stream processing with low latency, while Apache Spark is a more versatile framework that supports both batch and stream processing, along with other data processing tasks. read less